Optimal sensor selection for prediction-based iterative learning control of distributed parameter systems - Patan, Maciej (1975- ); Klimkowicz, Kamil; Patan, Krzysztof
The purpose of this study is to develop an effective computational scheme to solve the optimal tracking control problem for repeated trials in distributed-parameter system in the situation where quantity under control cannot be observed directly. In such situations, the reliability of model predictions becomes more important than the accuracy of model parameters, because the ultimate objective in model-based control is the prediction or forecast of the system states.
Keywords: iterative learning control; distributed parameter systems; optimal sensor selection